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Building Fabric: How I Automated Stakeholder Reports from GitHub

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Building Fabric: How I Automated Stakeholder Reports from GitHub
F
Software Engineer. Dark Souls | Stoicism | FullStack Engineering | Christianism | INFJ

I’ve always hated weekly meetings with non-technical stakeholders.

Explaining technical work is hard. If you’re experienced, you know the drill: don’t mention webhooks or backend code. You say, "We added payments so customers can buy items," and keep it moving.

But then comes the request nobody talks about: the written report.

In most small startups, there is no product manager. You have to write everything down for compliance or tracking. I found myself wasting hours re-reading my own code, checking the backlog, and filling out Notion pages to remember what I built.

It was a waste of time because everything I built was already logged in my Git history.

I wondered: If my work is already tracked in my commits and pull requests, why am I writing these reports manually?

So, I built a tool to do it for me.

That is how Fabric started. An AI engine that turns your GitHub activity into finished reports for your stakeholders.

Core Features

I focused on building a tool that handles the heavy lifting of reporting so you don't have to:

  • Deep Repository Sync: Goes beyond simple line counts. It extracts real-time commit metadata to capture the actual intent of your work.

  • Guided Onboarding: A clean, multi-step interface designed to get you set up quickly and reduce cognitive load.

  • The Transparency Engine: Generates high-fidelity Markdown reports focused on business outcomes.

  • Report Persistence: A centralized dashboard that lets you visualize and manage your historical reporting data.

  • Persona-Driven Synthesis: Features custom tone mapping, allowing you to tailor reports specifically for CTOs, Founders, or Board Members.

The Tech Stack

I kept the architecture simple to focus on the AI logic rather than managing complex infrastructure:

  • Next.js 16: The backbone of the application. Its speed and routing make it the perfect choice for a developer-focused tool.

  • Groq API: This is where the magic happens. I chose Groq for its incredibly fast inference speeds, which are essential when feeding it batches of commit logs for summarization.

  • Octokit: The official GitHub SDK. It handles the heavy lifting of interacting with the GitHub API.

  • Cloudflare R2: Fabric extracts screenshots from PRs and re-hosts them on R2 (S3-compatible) to keep your internal tooling private without relying on GitHub authentication.

What’s Next

Building Fabric has been about staying focused. To allow users to use Fabric faster, I’ve had to make some hard choices about what to ship later:

  • Platform Focus: Fabric is GitHub-only for now to prioritize the most common use cases. Support for GitLab and BitBucket is on the roadmap.

  • Security & Scaling: Currently, Fabric uses a simple, single-session experience without authentication. This lets individual developers and freelancers get immediate value without the friction of complex auth strategies.

Conclusion

I'm already working on part two of this series, where I’ll dive into the technical architecture, prompt engineering and the core features.

Fabric is available at: https://github.com/franciscoluna-28/fabric-ai

Follow my journey and see my other work at itsfranciscoluna.com.